Features for Discourse-New Referent Detection in Russian

Mention Detection for Improving Coreference Resolution in Russian Texts: A Machine Learning Approach

“…Thus, while the NP non-repetition or the head of an NP non-repetition in the previous context are relevant features for detecting both mentions classes, the unique NP or the unique head is much more likely for the former ones. In [35], 4 groups of features are tested for singletons detection: basic, structural, lexical, and (quasi-)syntactic features. Most of the features were proposed before for detecting singleton mentions in English (e.g.…”

“…[29,22]). Some other features, correlated with entity discourse role, were used in the first mention detection task (see also [35]). Thus, the set of features for DN detection should combine features for detecting non-anaphoricity with those that should have a correlation with the discourse role: non-coreferent mentions should be less important for the discourse.…”

“…[29,22]). Some other features correlated with entity discourse role are also used in the first mention detection task (section 4.3, see also [35]).…”

“…They both correlate with an entity importance in the discourse: the more important an entity is, the more words would be spent on it. These two features has theoretical motivation and showed great impact in the first mention detection task ( [35]), showing their correlation with a discourse role of a mention. Figure 2 shows the distribution of these features over a train set.…”